PhD: Predictive ML for Greenland Firn & Sea-Level Impact

Technical University of Denmark; Kongens Lyngby; On-site; DKK 320,000 - 350,000; Full time

Job summary

DTU Space invites applications for a PhD student in a FirnTip project that blends physics, mathematics, machine learning, and satellite data to predict when Greenland's firn stops storing meltwater and what that means for sea-level rise.

You will build models, apply them to climate scenarios, and collaborate with international partners to advance scientific computing and ML skills valued in research and industry.

Qualifications

• A master's degree in physics or mathematics, or a field with similar mathematical foundation.
• Experience writing scientific code from thesis or projects.
• Good knowledge of at least one: differential equations, numerical methods, statistics, or machine learning.
• Good written and spoken English.

Responsibilities

• Develop a framework predicting when Greenland's firn stops absorbing meltwater.
• Collaborate with supervisors at DTU Space and international partners.
• Identify climate factors controlling firn absorption, and combine satellite data with models.
• Develop machine-learning models that respect physical laws and signals of tipping points.
• Engage in teaching and knowledge-sharing within the DTU PhD program.

Skills

Physics/Math background

Scientific coding

English proficiency

Differential equations

Numerical methods

Statistics

Machine learning

Education

Master's degree in physics/mathematics

Tools

Graph neural networks

Remote sensing

Data assimilation

Job description

DTU Space invites applications for a PhD student in a FirnTip project that blends physics, mathematics, machine learning, and satellite data to predict when Greenland's firn stops storing meltwater and what that means for sea-level rise.

You will build models, apply them to climate scenarios, and collaborate with international partners to advance scientific computing and ML skills valued in research and industry.